FDTD-based Transcranial Magnetic Stimulation model applied to specific neurodegenerative disorders

CoSimPy: An open-source python library for MRI radiofrequency Coil EM/Circuit Cosimulation

BACKGROUND AND OBJECTIVES

The Electromagnetic/Circuit cosimulation method represents a valuable and effective strategy to address those problems where a radiative structure has to interact with external supporting circuitries. This is of particular concern for Magnetic Resonance Imaging (MRI), radiofrequency (RF) coils design, where the supporting circuitry optimisation represents, generally, a crucial aspect. This article presents CoSimPy, an open-source Python circuit simulation library for Electromagnetic/Circuit cosimulations and specifically optimised for MRI, RF coils design.

METHODS

CoSimPy is designed following an Object-orientated programming. In addition to the essential methods aimed to performed the Electromagnetic/Circuit cosimulations, many others are implemented both to simplify the standard workflow and to evaluate the RF coils performance. In this article, the theory which underlies the fundamental methods of CoSimPy is shown together with the basic framework of the library.

RESULTS

In the paper, the reliability of CoSimPy is successfully tested against a full-wave electromagnetic simulations involving a reference setup. The library is made available under https://github.com/umbertozanovello/CoSimPy together with a detailed documentation providing guidelines and examples. CoSimPy is distributed under the Massachusetts Institute of Technology (MIT) license.

CONCLUSIONS

CoSimPy demonstrated to be an agile tool employable for Electromagnetic/Circuit cosimulations. Its distribution is meant to fulfil the needs of several researchers also avoiding duplication of effort in writing custom implementations. CoSimPy is under constant development and aims to represent a coworking environment where scientists can implement additional methods whose sharing can represent an advantage for the community. Finally, even if CoSimPy is designed with special focus on MRI, it represents an efficient and practical tool potentially employable wherever electronic devices made of radiative and circuitry components are involved.

Numerical analysis of transcranial magnetic stimulation application in patients with orofacial pain

In this paper, we monitored the accuracy of non-navigated application of repetitive Transcranial Magnetic Stimulation (rTMS) in 10 patients suffering from orofacial pain by using functional magnetic resonance (fMRI), computer modeling and numerical simulation. Through a unique process, each fMRI scan was used to define a Region of Interest (ROI) where the source of the orofacial pain was located, which was to be stimulated using rTMS. For each patient, MRI scans with a spatial resolution of 0.7 mm were converted into an anatomically accurate head model. The head model including the ROI was then co-registered with a model of the stimulation coil in an electromagnetic field numerical simulator. The accuracy of rTMS application was evaluated based on the calculations of electric field intensity distribution in the ROI. The research has yielded unique insight into ROIs (with average volume 904mm3) in patients with orofacial pain and has also extended further possibilities of human head MRI image semi-automatic segmentation. According to the calculations performed, the average ROI volume that was stimulated by an electric field with an intensity of over 80 V/m was only 4.4%, with the maximum ROI volume being 20.5%. Furthermore, a numerical study of the impact of coil rotation and translation was performed. It demonstrated a) the optimal placement of the stimulation coil can significantly increase the volume of the stimulated ROI up to 60% and b) patients with orofacial pain would need precise coil positioning with a navigation error lower than 10 mm. Due to an acceptable proccessing time of up to 6 hours, described numerical simulation opens up new options for precise rTMS treatment planning. This planning platform together withpatient-specific navigated rTMS, could lead to significant increase of treatment outcomes in patients suffering from orofacial pain.

A fast tool for the parametric analysis of human body exposed to LF electromagnetic fields in biomedical applications

A numerical procedure for analyzing electromagnetic (EM) fields interactions with biological tissues is presented. The proposed approach aims at drastically reducing the computational burden required by the repeated solution of large scale problems involving the interaction of the human body with EM fields, such as in the study of the time evolution of EM fields, uncertainty quantification, and inverse problems. The proposed volume integral equation (VIE), focused on low frequency applications, is a system of integral equations in terms of current density and scalar potential in the biological tissues excited by EM fields and/or electrodes connected to the human body. The proposed formulation requires the voxelization of the human body and takes advantage of the regularity of such discretization by speeding-up the computational procedure. Moreover, it exploits recent advancements in the solution of VIE by means of iterative preconditioned solvers and ad hoc parametric Model Order Reduction techniques. The efficiency of the proposed tool is demonstrated by applying it to a couple of realistic model problems: the assessment of the peripheral nerve stimulation, performed in terms of evaluation of the induced electric field, due to the gradient coils of a magnetic resonance imaging scanner during a clinical examination and the assessment of the exposure to environmental fields at 50 Hz of live-line workers with uncertain properties of the biological tissues. Thanks to the proposed method, uncertainty quantification analyses and time domain simulations are possible even for large scale problems and they can be performed on standard computers and reasonable computation time. Sample implementation of the method is made publicly available at https://github.com/UniPD-DII-ETCOMP/BioMOR.

The development and modelling of devices and paradigms for transcranial magnetic stimulation

Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain, as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modelling.